Security in wireless networks is increasingly important. Wireless networks are formed of several nodes, each of which can be prone to attack or can be operated in a malicious manner. Thus, it is desirable to identify misbehaving nodes. Current research in the detection of misbehaving nodes in mobile wireless networks is still predominantly focused on adapting and optimizing conventional network defense strategies that concentrate on behaviors at the lower layers of the networking stack (see the List of Incorporated Literature References, Literature Reference Nos. 7 through 13). Research on strategies such as signature detection, statistical anomaly detection, and specification-based detection have proven effective for specific attack and network scenarios, but applicability to more general scenarios has proven to be elusive. What has been missing is a higher-level behavioral analysis of the entire networking stack and applications, on each node and on the network as a whole. It is this perspective that recent research in network science and information dynamics can now provide through the formulation and analysis of the graph-theoretic network-of-networks (NoN) model (see Literature Reference Nos. 14 through 16). Although NoN has been widely applied to the study of the dynamics of social networks, its application to cyber-security has only recently been recognized following breakthroughs of methods for modeling both logical and physical networks in NoN (see Literature Reference No. 17), where connectivity and dynamics are fundamentally different.
Thus, a continuing need exists for a system that extends the NoN model to the challenging environment of mobile wireless networks, particularly under real-world assumptions of scale and complexity.